BITS Faculty Publications

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Author: search.filters.author.Chamola, VinaySubject: search.filters.subject.Computer Science

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    HybridSecNet: In-Vehicle Security on Controller Area Networks Through a Hybrid Two-Step LSTM-CNN Model
    (IEEE, 2024-06) Alladi, Tejasvi; Chamola, Vinay
    The modern Intelligent Vehicle (IV) is a complex technological marvel that heavily relies on the Controller Area Network (CAN) bus system to enable seamless communication among different electronic control units (ECUs). However, the CAN bus system lacks security mechanisms for authentication and authorization, leaving it vulnerable to various attacks. Malicious actors can freely broadcast CAN messages without protection, making the system susceptible to DoS, Fuzzing, and Spoofing attacks. Therefore, it is crucial to devise methods to safeguard modern vehicles from such threats. In this research paper, we introduce HybridSecNet, A hybrid two-step LSTM-CNN Model for Intrusion Detection, a deep learning-based architecture specifically designed to bolster in-vehicle security on Controller Area Networks (CAN). HybridSecNet comprises two stages of classification: the first stage employs long short-term memory (LSTM) to categorize input data as either normal or attacked, and the second stage further classifies the attacks into specific types using Convolutional Neural Networks (CNN). This two-step approach significantly enhances classification accuracy and reliability, yielding remarkable results with accuracy, precision, recall, and an F1-score of approximately 99.5% for CAN bus network attacks. Comparative analyses with existing single-step models underscore the superiority of our proposed model, demonstrating its potential to revolutionize in-vehicle security in the realm of modern intelligent vehicles.
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    Artificial Intelligence-Empowered Optimal Roadside Unit (RSU) Deployment Mechanism for Internet of Vehicles (IoV)
    (IEEE, 2022) Gupta, Shashank; Chamola, Vinay
    Currently, the world is witnessing a huge growth in additional computing proficiency and extensive network coverage capability, which resulted in a paradigm shift from VANETs to Internet of Vehicles (IoV). Moreover, enhanced network capabilities facilitate enabling of IoV technology for latency-critical applications in energy-constrained smart IoT devices. However, IoV networks demand energy efficiency due to its dynamic nature for which Roadside Units (RSUs) are critical. However, in cities, huge deployment of RSUs and their maintenance is expensive in IoV infrastructure, requiring a trade-off between the network coverage and installation-related expenses. Also, the latency issues in IoV are highly dependent on the positioning of accessible RSUs. Motivated by the above highlighted issues, we propose an upgraded RSU placement method to boost network efficiency through placement of RSUs in optimal locations in a given road map. The Memetic Framework-based Optimal RSU Deployment (MFRD) algorithm is proposed to maximize the coverage area among the vehicles in an IoV and minimize the overlap in the coverage of the different RSUs. We observed from simulation results based on real-world maps that MFRD yields a significantly higher fitness score as compared to the existing state-of-the-art in terms of optimal positioning of the RSUs.
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    Role of machine learning and deep learning in securing 5G-driven industrial IoT applications
    (Elsevier, 2021-12) Chamola, Vinay; Gupta, Shashank
    The Internet of Things (IoT) connects millions of computing devices and has set a stage for future technology where industrial use cases like smart cities and smart houses will operate with minimal human intervention. IoT’s cross-domain amalgamations with emergent technologies like 5G and blockchain affects human life. Hence, increase in reliance over IoT necessitates focus on its privacy and security concerns. Implementing security through encryption, authentication, access control and communication security is the need of the hour. These needs can be best catered with the use of machine learning (ML) and deep learning (DL) that can help in realizing secure intelligent systems. In this work, the authors present a comprehensive review for securing Industrial-IoT (I-IoT) devices to contribute to the development of security methods for I-IoT deployed over 5G and blockchain. The survey provides a general analysis of the state-of-the-art security implementation and further assesses the product life cycle of IoT devices. The authors present numerous virtues as well as faults in the machine learning and deep learning algorithms deployed over the fog architecture in context with the security solutions. The potential security algorithms can help overcome many challenges in the IoT security and pave way for implementation with emerging technologies like 5G, blockchain, edge computing, fog computing and their use cases for creating smart environments.
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    Blockchain in Smart Grids: A Review on Different Use Cases
    (MDPI, 2019) Alladi, Tejasvi; Chamola, Vinay
    With the integration of Wireless Sensor Networks and the Internet of Things, the smart grid is being projected as a solution for the challenges regarding electricity supply in the future. However, security and privacy issues in the consumption and trading of electricity data pose serious challenges in the adoption of the smart grid. To address these challenges, blockchain technology is being researched for applicability in the smart grid. In this paper, important application areas of blockchain in the smart grid are discussed. One use case of each area is discussed in detail, suggesting a suitable blockchain architecture, a sample block structure and the potential blockchain technicalities employed in it. The blockchain can be used for peer-to-peer energy trading, where a credit-based payment scheme can enhance the energy trading process. Efficient data aggregation schemes based on the blockchain technology can be used to overcome the challenges related to privacy and security in the grid. Energy distribution systems can also use blockchain to remotely control energy flow to a particular area by monitoring the usage statistics of that area. Further, blockchain-based frameworks can also help in the diagnosis and maintenance of smart grid equipment. We also discuss several commercial implementations of blockchain in the smart grid. Finally, various challenges to be addressed for integrating these two technologies are discussed.
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    Blockchain Applications for Industry 4.0 and Industrial IoT: A Review
    (IEEE, 2019) Alladi, Tejasvi; Chamola, Vinay
    The potential of blockchain has been extensively discussed in the literature and media mainly in finance and payment industry. One relatively recent trend is at the enterprise-level, where blockchain serves as the infrastructure for internet security and immutability. Emerging application domains include Industry 4.0 and Industrial Internet of Things (IIoT). Therefore, in this paper, we comprehensively review existing blockchain applications in Industry 4.0 and IIoT settings. Specifically, we present the current research trends in each of the related industrial sectors, as well as successful commercial implementations of blockchain in these relevant sectors. We also discuss industry-specific challenges for the implementation of blockchain in each sector. Further, we present currently open issues in the adoption of the blockchain technology in Industry 4.0 and discuss newer application areas. We hope that our findings pave the way for empowering and facilitating research in this domain, and assist decision-makers in their blockchain adoption and investment in Industry 4.0 and IIoT space.
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    Applications of blockchain in unmanned aerial vehicles: A review
    (Elsevier, 2020-06) Alladi, Tejasvi; Chamola, Vinay
    The recent advancement in Unmanned Aerial Vehicles (UAVs) in terms of manufacturing processes, and communication and networking technology has led to a rise in their usage in civilian and commercial applications. The regulations of the Federal Aviation Administration (FAA) in the US had earlier limited the usage of UAVs to military applications. However more recently, the FAA has outlined new enforcement that will also expand the usage of UAVs in civilian and commercial applications. Due to being deployed in open atmosphere, UAVs are vulnerable to being lost, destroyed or physically hijacked. With the UAV technology becoming ubiquitous, various issues in UAV networks such as intra-UAV communication, UAV security, air data security, data storage and management, etc. need to be addressed. Blockchain being a distributed ledger protects the shared data using cryptography techniques such as hash functions and public key encryption. It can also be used for assuring the truthfulness of the information stored and for improving the security and transparency of the UAVs. In this paper, we review various applications of blockchain in UAV networks such as network security, decentralized storage, inventory management, surveillance, etc., and discuss some broader perspectives in this regard. We also discuss various challenges to be addressed in the integration of blockchain and UAVs and suggest some future research directions.
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    SecAuthUAV: A Novel Authentication Scheme for UAV-Ground Station and UAV-UAV Communication
    (IEEE, 2020) Alladi, Tejasvi; Chamola, Vinay
    Unmanned Aerial Vehicles (UAVs) are becoming very popular nowadays due to the emergence of application areas such as the Internet of Drones (IoD). They are finding wide applicability in areas ranging from package delivery systems to automated military applications. Nevertheless, communication security between a UAV and its ground station (GS) is critical for completing its task without leaking sensitive information either to the adversaries or to unauthenticated users. UAVs are especially vulnerable to physical capture and node tampering attacks. Further, since UAV devices are generally equipped with small batteries and limited memory storage, lightweight security techniques are best suited for them. Addressing these issues, a lightweight mutual authentication scheme based on Physical Unclonable Functions (PUFs) for UAV-GS authentication is presented in this paper. The UAV-GS authentication scheme is extended further to support UAV-UAV authentication. We present a formal security analysis as well as old-fashioned cryptanalysis and show that our protocol provides various security features such as mutual authentication, user anonymity, etc, and is resilient against many security attacks such as masquerade, replay, node tampering, and cloning attacks, etc. We also compare the performance of our protocol with state-of-the-art authentication protocols for UAVs, based on computation, communication, and memory storage cost.
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    A Lightweight Authentication and Attestation Scheme for In-Transit Vehicles in IoV Scenario
    (IEEE, 2020-12) Alladi, Tejasvi; Chamola, Vinay
    With the rise of new technological paradigms such as the Internet of Things (IoT) and the Internet of Vehicles (IoV), we are going to see an unprecedented growth of connected vehicles on the roads. Also, with the ever-increasing complexity of vehicular electronics and with the increasing number of Electronic Control Units (ECUs) inside these next-generation vehicles, the need for verification of the firmware and software running on these ECUs using attestation techniques is heightened all the more. In this paper, we propose a lightweight and secure authentication and attestation scheme for attesting vehicles while they are on the roads. Since this attestation is proposed to be carried out on moving vehicles, there is also a need for authenticating the vehicles with the Road Side Units (RSUs) first before carrying out attestation. Therefore, a combined attestation and authentication scheme for verification of the vehicle ECU firmware is presented here. The ECU firmware running on the vehicles can be attested from the edge servers connected to the RSUs while the vehicles are in-transit and passing through these RSUs. We perform a security analysis of the proposed attestation and authentication protocol and compare it with other similar existing protocols. We also do a performance analysis of the proposed protocol and show the feasibility of its deployment.
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    PARTH: A two-stage lightweight mutual authentication protocol for UAV surveillance networks
    (Elsevier, 2020-07) Chamola, Vinay; Alladi, Tejasvi
    UAVs are being widely deployed in security and surveillance applications around the world. Due to deployment in remote environments and also due to limited resources on these devices, they are susceptible to device capture and physical tampering attacks. This heightens the risk of sensitive data stored in the UAVs to be captured by adversaries. To address this issue, a two-stage lightweight mutual authentication protocol is presented in this paper, well suited to SDN-backed multi UAV networks deployed in surveillance areas. Formal security proof of the protocol is presented to highlight its security features. We also compare our protocol with other state-of-the-art works in terms of computation latency and resilience against known security attacks.
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    Industrial Control Systems: Cyberattack trends and countermeasures
    (Elsevier, 2020-04) Alladi, Tejasvi; Chamola, Vinay
    It is generally understood that an attacker with limited resources would not be able to carry out targeted attacks on Industrial Control Systems. Breaking this general notion, we present case studies of major attacks on Industrial Control Systems (ICSs) in the last 20 years. The attacks chosen are the most prominent ones in terms of the economic loss inflicted, the potential to damage physical equipment and to cause human casualties. For each of these attacks, we describe the attack methodology used and suggest possible solutions to prevent such attacks. We analyze each case study to provide a better insight into the development of future cybersecurity techniques for ICSs. Finally, we suggest some recommendations on the best practices for protecting ICSs.